The course covers several advanced topics including a new history-conditioned forecasting workflow, proxy modeling techniques, and integrated modeling approaches using the MEPO plugin to Petrel.
The history-conditioned forecasting workflow was introduced with MEPO 4.2 and uses a Markov Chain Monte Carlo approach for estimating prediction uncertainties.
Proxy modeling methods can be useful for exploring the impact of different sets of input parameters before launching full field simulations. In this course we will introduce different proxy modeling techniques and discuss the performance potential in complex simulation studies.
Integrated modeling workflows are becoming more widely used, so this course also covers the use of the MEPO plugin to Petrel which extends the capability of MEPO to incorporate static models in optimization and uncertainty workflows.
Introduction to history-conditioned workflows and Markov Chain Monte Carlo techniques
Overview of response surface modeling (RSM) techniques
Use of proxy modeling for sensitivity and trend analysis
Structured methods for managing large history matching projects
MEPO-Petrel workflows using MEPO 4.2 and Petrel 2012/2013
Integrated modeling - linking external software tools such as geomodeling and pipeline modeling packages
Customization of pre- and post-processing tasks using Python scripts
• Introduction to history-conditioned forecasting workflows – MCMC and proxy modeling methods
• Response Surface Modeling (RSM)
• Managing History Matching Projects – quality control and structured workflow techniques
• MEPO – Petrel workflows in MEPO 4.2 / Petrel 2013
• How to link to external software tools for integrated workflows, e.g. include geo modeling or surface pipeline networks
• Introduction to Python scripting
Knowledge of ECLIPSE reservoir simulator. MEPO Introduction course.